// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#pragma once

#include "ngraph/op/util/binary_elementwise_arithmetic.hpp"

namespace ngraph {
namespace op {
namespace v1 {
/// \brief Elementwise division operation.
class NGRAPH_API Divide : public util::BinaryElementwiseArithmetic {
public:
    NGRAPH_RTTI_DECLARATION;
    /// \brief Constructs a division operation.
    Divide() : util::BinaryElementwiseArithmetic(AutoBroadcastSpec::NUMPY) {}

    /// \brief Constructs a division operation.
    ///
    /// \param arg0 Node that produces the first input tensor.
    /// \param arg1 Node that produces the second input tensor.
    /// \param pythondiv Use Python style rounding for integral type
    /// \param auto_broadcast Auto broadcast specification
    Divide(const Output<Node>& arg0,
           const Output<Node>& arg1,
           bool pythondiv,
           const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));

    /// \brief Constructs a division operation.
    ///
    /// \param arg0 Node that produces the first input tensor.
    /// \param arg1 Node that produces the second input tensor.
    /// \param auto_broadcast Auto broadcast specification
    Divide(const Output<Node>& arg0,
           const Output<Node>& arg1,
           const AutoBroadcastSpec& auto_broadcast = AutoBroadcastSpec(AutoBroadcastType::NUMPY));
    bool visit_attributes(AttributeVisitor& visitor) override;
    bool is_pythondiv() const {
        return m_pythondiv;
    }
    void set_is_pythondiv(bool pythondiv) {
        m_pythondiv = pythondiv;
    }
    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;

    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
    bool has_evaluate() const override;

protected:
    bool m_pythondiv{true};
};
}  // namespace v1
}  // namespace op
}  // namespace ngraph
